BELIEF UPDATING BY NETWORK PROPAGATION
Publisher Summary
In a large class of networks, coherent and stable probabilistic reasoning can be accomplished by local propagation mechanisms, keeping the weights on the links constant throughout the process. This is done by characterizing the belief in a proposition by a list of parameters, each representing the degree of support the host proposition obtains from one of its neighbors. Maintaining such a record of the sources of belief facilitates local updating of beliefs and that the network relaxes to a stable equilibrium, consistent with the axioms of probability theory, in time proportional to the network diameter. Such a record of parameters is also postulated as a mechanism that permits ...
Get Probabilistic Reasoning in Intelligent Systems now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
